What is R programming?

R programming is the use of the R computer language for statistical analysis and graphic presentation. R is commonly used in business and research computing environments to analyze and visualize data, then create reports that can be used for decision making. R programming is increasingly more important given the expansion of big data for analysis.

Why learn R programming?

It's important to learn R programming if you want to be able to build computer programs that wrangle data and convert it into usable information. Organizations often have large amounts of data but are unable to understand what it means. Using programs written by R, you can generate Bayesian statistics and graphic analysis for business analytics, public health, and medical research, among other industries. Learning R is a component of learning data science, so another reason to study R programming is to get some of the fundamentals completed before venturing deeper into computer science studies.

What are typical careers that use R programming?

Typical careers that use R programming are in business analytics, financial services, and medical research. It is also a skill used in many data science roles. R programming pulls out information from large sets of data, so any field that calls for statistical inference from big data needs competent R programmers to create the analytics and reports needed. Some experience with R programming is useful for people who will be managing programming teams or requesting reports made from programs written in R. As big data analysis becomes more important in more fields, R programming becomes more valuable in the workplace.

How can online courses help me learn R programming?

Online courses can help you learn R programming by introducing the fundamentals of the language, teaching how it connects to such industries as finance and health care, and offering projects that let you show what you have learned. Courses are offered at all levels, from beginning to advanced. Many of them set you up for further work in data science or allow you to earn a specialization or certificate.

What are the benefits of taking an online R Programming course?

Online R Programming courses offer a convenient and flexible way to enhance your knowledge or learn new R Programming skills. Choose from a wide range of R Programming courses offered by top universities and industry leaders tailored to various skill levels.

What R Programming courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in R Programming, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top R Programming Courses - Learn R Programming Online

Explore the R Programming Course Catalog

The University of Edinburgh
Code Yourself! An Introduction to Programming
Skills you'll gain: Software Engineering, Video Game Development, Software Testing, Software Development, Programming Principles, Software Design, Game Design, Computer Programming, Animation and Game Design, Debugging, Computational Thinking, Algorithms
4.7
Rating, 4.7 out of 5 stars
3.6K reviews
Beginner · Course · 1 - 3 Months
Universidad Nacional Autónoma de México
Introducción a Data Science: Programación Estadística con R
Skills you'll gain: R Programming, Statistical Programming, Ggplot2, Data Manipulation, Simulations, Statistical Software, Data Science, Data Visualization, Graphing, Programming Principles, Data Import/Export, Scripting, Data Structures, Software Installation, Package and Software Management
4.7
Rating, 4.7 out of 5 stars
8.5K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
IBM
Applied Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Visualization, Predictive Modeling, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Jupyter, Matplotlib, Pandas (Python Package), Seaborn, Data Presentation, Data Import/Export, Web Scraping, Python Programming, Data Structures, Data Science, Data-Driven Decision-Making
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
59K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
Johns Hopkins University
Data Science
Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr
4.5
Rating, 4.5 out of 5 stars
51K reviews
Beginner · Specialization · 3 - 6 Months
University of California San Diego
Biology Meets Programming: Bioinformatics for Beginners
Skills you'll gain: Bioinformatics, Programming Principles, Molecular Biology, Python Programming, Computational Thinking, Biology, Algorithms, Data Structures
4.2
Rating, 4.2 out of 5 stars
1.6K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
University of Colorado Boulder
R Programming and Tidyverse Capstone Project
Skills you'll gain: R Programming, Rmarkdown, Tidyverse (R Package), Ggplot2, Data Import/Export, Data Analysis, Data Visualization Software, Data Science, Data Manipulation, Data Storytelling, Statistical Analysis, Data Cleansing, Data Integration, Data Transformation
4.7
Rating, 4.7 out of 5 stars
6 reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
Johns Hopkins University
The R Programming Environment
Skills you'll gain: Tidyverse (R Package), Web Scraping, Data Manipulation, R Programming, Data Transformation, Data Cleansing, Data Science, Big Data, Text Mining, Data Import/Export, Programming Principles, Data Structures, Performance Tuning, Debugging, Application Programming Interface (API)
4.3
Rating, 4.3 out of 5 stars
1.2K reviews
Intermediate · Course · 1 - 3 Months
University of Washington
Programming Languages, Part A
Skills you'll gain: Software Installation, Programming Principles, Other Programming Languages, Functional Design, Ruby (Programming Language), Software Design Patterns, Computational Thinking
4.9
Rating, 4.9 out of 5 stars
1.9K reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Packt
Foundations of R Programming and Basic Data Manipulation
Skills you'll gain: Rmarkdown, Data Import/Export, R Programming, Data Manipulation, Data Visualization, Web Scraping, Ggplot2, Plotly, Programming Principles, Tidyverse (R Package), Data Visualization Software, Data Wrangling, Data Cleansing, Statistical Programming, Data Transformation, Data Structures, Scripting Languages, Scripting, Development Environment
Beginner · Course · 1 - 3 Months
Packt
R Programming for Statistics and Data Science
Skills you'll gain: R Programming, Statistical Hypothesis Testing, Ggplot2, Data Visualization, Data Manipulation, Exploratory Data Analysis, Tidyverse (R Package), Statistical Modeling, Data Analysis, Regression Analysis, Data Structures, Data Wrangling, Statistical Analysis, Descriptive Statistics, Programming Principles, Data Transformation, Statistical Inference, Probability & Statistics
4.5
Rating, 4.5 out of 5 stars
6 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Duke University
Introduction to Probability and Data with R
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Software, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.8K reviews
Beginner · Course · 1 - 3 Months
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Data Collection, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
4.1K reviews
Beginner · Course · 1 - 3 Months